Our ability to understand and interact with our visual environment depends critically on brain mechanisms for transforming the eye image into knowledge about objects. Understanding this transformation would provide a rational basis for designing future generations of prosthetic neural implants for blind subjects that could deliver rich and useful object information. It would also impact clinical approaches to higher-order perceptual impairments produced by stroke or genetic disorders like autism. The neural transformation of object information can be studied at a detailed, mechanistic level by means of electrode recording from individual neurons in the brains of non-human primates, in which the organization of the object-processing pathway is similar to humans. Previous studies have focused separately on different levels of object information at early, intermediate, or late processing stages in this pathway. The long-term goal of this study is to discover how each of these levels is transformed into the next by synthesizing signals for simple image elements into increasingly complex and abstract representations. The novel approach proposed for this funding period is to study these different levels of object information simultaneously in order to infer transformation mechanisms. This requires searching an unprecedented range of stimuli, which can be accomplished by using an evolutionary search strategy. Stimulus evolution is controlled by a genetic algorithm for creating mutated descendants from stimuli that evoke strong responses from the neuron being studied. This moves the experiment quickly toward the region of interest in stimulus space. We will use this strategy to explore (1) how simple orientation/frequency signals are synthesized to produce neural selectivity for complex contour geometry, (2) how geometric part signals are synthesized to produce neural selectivity for familiar objects like faces and bodies, and (3) how geometric shape information is transformed into online knowledge about object characteristics. These experiments will help link previous results into a more coherent picture of the multi-stage transformation from eye images to object knowledge. RELEVANCE TO PUBLIC HEALTH: This study will help explain how the brain transforms eye image information into knowledge about visual objects. The results are relevant to the design of prosthetic neural implants for blind subjects and to understanding visual impairments due to stroke or genetic disorders.